Hidden Markov models for feeding data from groups of red deer

R.P Littlejohn

A. Bryant

I.D. Corson

We present an analysis of datasets consisting of start/stop times of individual deer feeding episodes over several days of continuous automated observation. Feeding episodes occur in clusters which constitute 'meals', during which the deer is primarily feeding, while at other times it is engaged in some other activity. Individuals within the group tend to have their meals at the same time. Since activity is not observed, but only whether or not each animal is feeding, this suggests that a hidden Markov or semi-Markov model could be used to analyse the data. Such models for individual cattle, but with no group context, have been used by Allcroft et al (2004). We also consider a generalization including feedback given by Zucchini et al (2005).

Session 3c, Environmetrics: 14:55 — 15:15, Room 445

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